Download PDF
Methods Inf Med 1990; 29(01): 30-40
DOI: 10.1055/s-0038-1634764
Knowledge-based systems
Schattauer GmbH

Proposed Methodology for Knowledge Acquisition: A Study on Congenital Heart Disease Diagnosis

F. B. Leãot
1   Institute de Cardiologia do Rio Grande do Sul, Porto Alegre, Brazil
,
F. A. Rocha
2   Centro de Informática em Saúde da Escola Paulista de Medicina, São Paulo, Brazil
› Author AffiliationsThe authors express their gratitude to Prof. M. L. Leāo for the revision of the English text, as well as to Ms. Helena Rossi for the proper organization of the bibliography.
Further Information

Publication History

Publication Date:
06 February 2018 (online)

    Permissions and Reprints

Abstract

“Knowledge and human power are synonymous, since the ignorance of the cause frustrates the effect:…“

Francis Bacon1

This paper proposes a methodology for knowledge acquisition (KA) from multiple experts, in an attempt to elicit the heuristic rules followed by the physician in diagnosing twelve frequently occurring congenital heart diseases (CHD). Twenty-two pediatric cardiologists and twenty-three general cardiologists were interviewed with this technique; 274 interviews were conducted, 169 with the 22 experts, 105 with the 23 non-experts. A graph formalism was employed to represent their reasoning model, leading to the construction of a “mean reasoning model” for each diagnosis, separately for experts and non-experts. The results indicate that experts, compared to non-experts, tend to build knowledge representation models (KRM) that are smaller and less complex. Qualitative differences in information utilization between the two groups were also observed. Entropy analysis suggests a greater objectivity and cohesion of the experts’ model.

Key-Words

Knowledge Acquisition - Expert Systems - Heuristic Learning - Reasoning Models
 

  • REFERENCES

  • 1 Barr A, Cohen P R, Feigenbaum E A. Handbook of Artificial Intelligence (Vols 1-3). Los Altos Calif: Kaufmann; 1981/82.
    Google Scholar
  • 2 Buchanan B G, Shortliffe E H. The context of the Mycin experiments. In: Rule- Based. Expert Systems. The Mycin Experiments of the Stanford Heuristic Programming Project. Reading: Addison-Wesley Publ Comp; 1985: 3-19.
    Google Scholar
  • 3 Clancey W J. The epistemology of a rule- based expert system - a framework for explanation. Art Intell 1983; 20: 215-51.
    CrossrefPubMedGoogle Scholar
  • 4 Duda R O, Shortliffe E H. Expert systems research. Science 1983; 220: 261-8.
    CrossrefPubMedGoogle Scholar
  • 5 Hayes-Roth F, Waterman D A, Lenat B D. An overview of expert systems. In: Building Expert Systems. Hayes-Roth F, Watermann D A, Lenat B D. Reading Mass: Addison-Wesley Publ Comp; 1983: 3-30.
    Google Scholar
  • 6 Kingsland L C, Lindberg DAB, Sharp G C. Anatomy of a knowledge-based consultant system: AI/Rheum.M. D.. Computing 1986; 03: 18-26.
    PubMedGoogle Scholar
  • 7 Miller R, Masarie F, Myers J D. Quick Medical Reference (QMR) for diagnostic assistance. M. D.. Computing 1986; 03: 34-48.
    PubMedGoogle Scholar
  • 8 Miller R, Pople H, Myers J. INTERNIST- 1 an experimental computer-based diagnostic consultant for general internal medicine. N Engl J Med 1982; 307: 468-76.
    CrossrefPubMedGoogle Scholar
  • 9 Nilsson N J. Principles of artificial intelligence. Palo Alto Calif: Tioga; 1980
    Google Scholar
  • 10 Shortliffe E H, Buchanan B G, Feigenbaum E A. Knowledge engineering for medical decison making: a review of computer-based clinical decision aids. Proc IEEE 1979; 67: 1207-24.
    CrossrefPubMedGoogle Scholar
  • 11 Anderson H. Why artificial intelligence isn’t (yet). AI Expert 1987; 02: 36-44.
    PubMedGoogle Scholar
  • 12 Canning R C. What’s happening with expert systems?. EDP ANALYZER 1985; 23: 1-15.
    PubMedGoogle Scholar
  • 13 Friedman R B, Gustafson D H. Computers in clinical medicine: a critical review (editorial). Comp Biomed Res 1977; 10: 199-204.
    CrossrefPubMedGoogle Scholar
  • 14 Kinney E L. Medical expert systems - who needs them?. (editorial) CHEST 1987; 91: 3-4.
    CrossrefPubMedGoogle Scholar
  • 15 Reggia J A, Tuhrim S. An overview of methods for computer-assisted medical decision making. In: Computer-Assisted Medical Decision Making. Reggia J A, Tuhrim S. eds. New York: Springer Verlag; 1985: 45.
    Google Scholar
  • 16 Sandell H S H, Bourne J R. Expert system in medicine: a Biomedical Engineering perspective. Crit Rev Biomed Eng 1985; 12: 95-129.
    PubMedGoogle Scholar
  • 17 Schwartz W B, Patil R S, Szolovits P. Artificial intelligence in medicine. Where do we stand?. N Engl J Med 1987; 316: 685-8.
    CrossrefPubMedGoogle Scholar
  • 18 De Greef P, Breuker J. A case study in structured knowledge acquisition. In: Proceedings of UCAI-9. Los Angeles: 1985
    Google Scholar
  • 19 Ericsson K A, Simon H A. Verbal reports as data. Psychol Rev 1980; 87: 215-51.
    CrossrefPubMedGoogle Scholar
  • 20 Finin T W. Interactive classification; a technique for acquiring and maintaining knowledge bases. In: Proc IEEE: 1986: 914-21.
    Google Scholar
  • 21 Goncalves CA. Aquisicāo e representaçāo de conhecimento para sistemas especialis- tas (Doctoral thesis). FEA/USP. 1986
    PubMedGoogle Scholar
  • 22 Grover M D. A pragmatic knowledge acquisition methodology. Proceedings of IJCAI-8, Karlsruhe. In: 1983
    PubMedGoogle Scholar
  • 23 Haley P, Williams C. Expert system development requires knowledge engineering. Comput Design 1986; 25: 83-8.
    PubMedGoogle Scholar
  • 24 Hoffman R R. The problem of extracting the knowledge of experts from the perspective of experimental psychology. AI Magazine 1987; 08: 53-67.
    PubMedGoogle Scholar
  • 25 Johnson P E. What kind of expert should a system be?. J Med Philos 1983; 08: 11-91.
    PubMedGoogle Scholar
  • 26 Kassirer J P, Kuipers B J, Gorry G A. Towards a therory of clinical expertise. Am J Med 1982; 73: 251-9.
    CrossrefPubMedGoogle Scholar
  • 27 Kolodner J L. Towards an understanding of the role of experience in the evolution from novice to expert. Int J Man-Machine Stud 1983; 19: 497-518.
    PubMedGoogle Scholar
  • 28 Kolodner J, Kolodner R M. Using experience in clinical problem solving: introduction and framework. IEEE Trans Syst Man C. ybcrn 1987; SCM-17: 420-31.
    PubMedGoogle Scholar
  • 29 Kulikowsky C A. Problems in the design of knowledge bases for medical consultation. In: Computer-Assisted Medical Decision Making. Reggia A J, Tuhrim S. eds. New York: Springer-Verlag; 1985: 38-48.
    Google Scholar
  • 30 Larkin J, McDermott J, Simon D P, Simon H A. Expert and novice performance in solving physics problems. Science 1980; 208: 1335-42.
    CrossrefPubMedGoogle Scholar
  • 31 Leão B. Construcāo da base de conhecimento de um sistema especialista de apoio ao diagnóstico das cardiopatias congênitas (Ph D Thesis). Sāo Paulo: Escola Paulista de Medicina; 1988
    Google Scholar
  • 32 Leāo B F, Lucchese F A, Rocha A F. A methodology proposal of knowledge acquisition. In: Proc Seventh Intern Congr Med Inform Europe, Rome 1987; 1042-50.
    PubMedGoogle Scholar
  • 33 Leāo B F, Rocha A F. Medical knowledge representation - a case study. Second IFSA Congress, Tokyo 1987; 376-9.
    PubMedGoogle Scholar
  • 34 Michaelsen R H, Michie D, Boulanger A. The technology of expert systems - transplanting expert knowledge to machines. Byte 1985; 10: 303-12.
    PubMedGoogle Scholar
  • 35 Mittal S. Knowledge acquisition from multiple experts. AI Magazine 1985; 06: 32-6.
    PubMedGoogle Scholar
  • 36 Prerau D S. Knowledge acquisition in the development of a large expert system. AI Magazine 1987; 08: 43-51.
    PubMedGoogle Scholar
  • 37 Shachter R, Heckerman D E. Thinking backward for knowledge acquisition. AI Magazine 1987; 07: 55-61.
    PubMedGoogle Scholar
  • 38 Van Bemmel J H. Formalization of medical knowledge. Meth Inform Med 1986; 25: 191-3.
    PubMedGoogle Scholar
  • 39 Van Bemmel J H. Formalization of medical knowledge, the basis for diagnostic strategies and expert systems. In: Van Bemmel G J, Grémy F, Zvarova J. eds. Medical Decision Making: Diagnostic Strategies and Expert Systems.. Amsterdam: North-Holland Publ Comp; 1985: 1-11.
    Google Scholar
  • 40 Wielinga B J, Breuker J A. Interpretation of verbal data for knowledge acquisition. In: O’Seha T. Advances in Artificial Intelligence. Amsterdam: North-Holland Publ Comp; 1985: 3-12.
    Google Scholar
  • 41 Wright G, Ayton P. Eliciting and modelling expert knowledge. Dec Supp Syst 1987; 03: 13-26.
    CrossrefPubMedGoogle Scholar
  • 42 Kassirer J P, Gorry G A. Clinical problem solving: a behavioral analysis. Ann Intern Med 1978; 89: 245-55.
    CrossrefPubMedGoogle Scholar
  • 43 Roch A F. Toward a theoretical and experimental approach of fuzzy learning. In: Gupta M M, Sanchez E. eds. Approximate Reasoning in Decision Analysis. Amsterdam: North-Holland Publ Comp; 1982: 191-9.
    Google Scholar
  • 44 Haray F. Graph Theory. Reading mass: Addison-Wesley Publ Comp; 19872: 8-40.
    Google Scholar